Coil selection in multi-coil wireless charging system

ABSTRACT

A wireless charging system is configured to charge one or more receiver devices simultaneously. The wireless charging system includes a plurality of coils for wireless charging the one or more receiver devices. The wireless charging system may use a machine learning algorithm to detect the one or more receiver devices and select which of the multiple coils to activate for charging the multiple coils. Based on measurements made from signal through the coils within the wireless charging system, the machine learning algorithm determines a subset of the coils to activate for charging the detected one or more receiver devices.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application claims the benefit of U.S. Patent Application62/834,919, which was filed Apr. 16, 2019, which is hereby incorporatedby reference in its entirety.

TECHNICAL FIELD

The disclosure relates to wireless charging systems, and moreparticularly to multi-coil wireless charging systems.

BACKGROUND

With growing popularity of wireless devices, efficient wireless chargingsystem for simultaneously charging a variety of wireless devices (e.g.,cellphone, tablet, speaker, watch, headphones, IoT device) is useful.Having a single wireless charging system that can simultaneously chargemultiple devices eliminates the inconvenience of managing multiplechargers.

A wireless charging system may be configured to charge multiple wirelessdevices simultaneously. The wireless charging system may include acharging surface on which wireless devices are placed to be charged. Thewireless charging system may provide high degree of flexibility in thepositioning of the devices on the charging surface by allowing devicesto be placed at any location on the charging surface instead ofrestricting it to a specific location. However, because devices may beplaced at different locations on the charging surface, it is challengingto determine how to drive the wireless charging system efficiently forall possible device placements. Additionally, some users cover theirdevices with protective cases or attach accessories such as phone standsor card holders to the back of their devices, which increases thedistance between the charging surface of the wireless charging systemand the receiver coils in the devices. Inductive charging used bywireless charging systems is based on distance between transmissioncoils and receiver coils, and the increase in distance between thetransmission coils and the receiver coils adds another challenge forwireless charging systems because the coupling between the coils growsweaker with distance.

SUMMARY

A wireless charging system with multiple transmission coils allows forsimultaneous charging of receiver devices by independently controllingeach of the multiple transmission coils. The multiple transmission coilsmay be arranged in an array within the wireless charging system and eachcoil may be independently controlled by a coil drive system that outputsa driving signal to the coil. The driving signal may be selected basedon target characteristics of the coil determined using a feedback systemthat includes one or more feedback channels. In some embodiment, a firstfeedback channel may be high precision measurements of voltage acrossthe coils or current through the coils, and a second feedback channelmay be communication signals from the receiver devices. Based on thefirst feedback channel and the second feedback channel, the wirelesscharging system determines how to drive a subset of the transmissioncoils for charging one or more receiver devices on the wireless chargingsystem. The wireless charging system may detect the one or more receiverdevices to be charged and select the subset of transmission coils forcharging the detected one or more receiver devices, for example, using amachine learning algorithm.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a system diagram of a wireless charging system, in accordancewith an embodiment.

FIG. 2 is a system diagram of a microcontroller and a coil drivingmodule of FIG. 1, in accordance with an embodiment.

FIG. 3A is a first example of a coil drive circuit, in accordance withan embodiment.

FIG. 3B is a second example of a coil drive circuit including a loadswitch, in accordance with an embodiment.

FIG. 4 is a third example of a coil drive circuit, in accordance with anembodiment.

FIG. 5 is a flowchart illustrating a process of driving a coil, inaccordance with an embodiment.

FIG. 6 is an example of a coil measurement circuit, in accordance withan embodiment.

FIG. 7 is a flowchart illustrating a process of performing digitalprocessing on samples of a signal from a coil, in accordance with anembodiment.

FIG. 8 is an example encoding of a communication signal in a receiverdevice, in accordance with an embodiment.

FIG. 9 is a block diagram of a circuit for demodulating a signal from areceiver device, in accordance with an embodiment.

FIG. 10 is a flowchart illustrating a process of demodulating a signalfrom a receiver device, in accordance with an embodiment.

FIG. 11 is an example layout of multiple coils in a wireless chargingsystem, in accordance with an embodiment.

FIG. 12 is a block diagram of a pulse width modulation (PWM) controlsystem, in accordance with an embodiment.

FIG. 13 illustrates an example process of deploying a classificationmodel for receiver device detection, in accordance with an embodiment.

FIG. 14 illustrate a flowchart illustrating a process of training amachine-learned model, in accordance with an embodiment.

The figures depict various embodiments for purposes of illustrationonly. One skilled in the art will readily recognize from the followingdiscussion that alternative embodiments of the structures and methodsillustrated herein may be employed without departing from the principlesdescribed herein.

DETAILED DESCRIPTION

The language used in the specification has been principally selected forreadability and instructional purposes, and it may not have beenselected to delineate or circumscribe the patent rights. It is thereforeintended that the scope of the patent rights be limited not by thisdetailed description, but rather by any claims that issue on anapplication based hereon. Accordingly, the disclosure of the embodimentsis intended to be illustrative, but not limiting, of the scope of thepatent rights, which is set forth in the following claims.

Configuration Overview

A wireless charging system for charging one or more receiver devicesincludes a plurality of coils, where each coil is driven independently.Each coil receives a coil driving signal from a coil drive circuit, andthe coil driving signal is generated based on target characteristicssuch as a target frequency, a target amplitude, and a target phase.Based on the target characteristics, a frequency and a duty cycle isdetermined for a pulse width modulation (PWM) that is provided as aninput to a circuit that generates the coil driving signal as an outputto a coil. The circuit may include a half-bridge inverter or afull-bridge inverter.

The wireless charging system may use a first feedback channel indetecting receiver devices. One of the feedback channels may be based onmeasurements of a signal in a coil of the plurality of coils made usingan analog to digital converter (ADC). The sampling speed and digitalFourier transform size for the measurements is selected to avoidcollisions of harmonic signals.

Another of the feedback channels may be demodulated communicationsignals from receiver devices being charged by the wireless chargingsystem. The communication signals may be according to Qi standards. Thecurrent in the coils of the wireless charging system is a function ofreceiver load in the receiver devices, and the receiver devices encodethe communication signals by varying the receiver load (e.g., by turninga switch that changes the receiver load ON and OFF). The wirelesscharging system analyzes the current in the coils of the wirelesscharging systems and demodulates the communication signals based onchanges in the current. The wireless charging system further performserror correction on the demodulated communication signals for improvingaccuracy.

The wireless charging system detects one or more receiver devices anddetermines which subset of the plurality of coils to activate forcharging the detected one or more receiver devices. The wirelesscharging system may use a machine learning algorithm to determine thesubset of coils. The machine learning algorithm receives an input datavector based on signals from the plurality of coils and identifies acharging configuration based on the input data vector. The chargingconfiguration identifies the subset of coils to be used in charging theone or more receiver devices.

Overview of Wireless Charging System

Referring now to Figure (FIG. 1, shown is a system diagram of a wirelesscharging system 100 in accordance with an example embodiment. Thewireless charging system 100 includes an AC/DC adaptor 105 that isconnected to a power management module 110. The AC/DC adaptor 105 isconnected to an external power source 155 (e.g., wall plug) and convertsalternating current (AC) from the external power source 155 into directcurrent (DC) for powering modules in the wireless charging system 100.Using the DC output from the AC/DC adaptor 105, the power managementmodule 110 supplies power to a WiFi module 115, user interface (UI)module 120, a thermal control module 125, a microcontroller 130, a coildriving module 135, a universal serial bus (USB) module 140 of thewireless charging system 100, and a storage 145. It is noted that inalternative embodiments, different and/or additional components may beincluded in the system.

The WiFi module 115 connects with a data cloud for additional controland analytical functionalities that may not be performed by a lesssophisticated microcontroller 130 that has limited computing power. TheWiFi module 115 may include a WiFi controller that manages communicationbetween the microcontroller 130 and the cloud. The WiFi module 115 mayconnect to the cloud via a WiFi antenna.

The UI module 120 manages interactions between a user and the wirelesscharging system 100 by receiving signals from a user and sending thesignals to the microcontroller 130 and receiving signals from themicrocontroller 130 and sending the signals to the user. The UI module120 may include input hardware such as a button, a switch, a microphone,a touch interface, and the like that the user may interact with toprovide input to the microcontroller 130. The wireless charging system100 may also include output hardware such as LEDs, a speaker, a displayscreen, and the like to communicate a message to the user. For example,the UI module 120 may cause a light emitting diode (LED) to be in astate to flash or remain in a green light when charge is complete for adevice connected to the wireless charging system 100, be in a state toflash or remain in a red light when charging, and be in a state to blinkrapidly in a red light when there is an error.

The thermal control module 125 monitors temperature of the wirelesscharging system 100 to ensure safe operating conditions for the wirelesscharging system 100. The thermal control module 125 may includetemperature monitoring sensors such as thermistors to determine when atemperature of the wireless charging system 100 exceeds a threshold thatrepresents a safe temperature for the wireless charging system 100. Thethermistors may be connected to the microcontroller 130, and themicrocontroller 130 determines the temperature of the wireless chargingsystem 100 based on resistance in the thermistors. The thermal controlmodule 125 may include a fan controlled by the microcontroller 130. Whenthe microcontroller 130 determines that the temperature exceeds thethreshold, the microcontroller 130 may activate the fan until thetemperature returns to below the safe threshold.

The microcontroller 130 may be configured to automatically control theWiFi module 115, UI module 120, the thermal control module 125, the coildriving module 135, and the USB module 140. The microcontroller 130 maybe an integrated circuit chip with one or more central processing units(CPUs), memory, and input/output ports that provides instructions to itsconnected modules. The microcontroller 130 can be any controller orprocessor for executing program instructions which include states. Theinstructions may be stored in a machine-readable medium. Theinstructions may also reside, completely or at least partially, within amemory within the microcontroller 130 or stored in a cloud andtransmitted to the microcontroller 130 over a network.

The coil driving module 135 includes a coil that charges a receiverdevice 150A using wireless power transfer and a control system for thecoil. The coil driving module 135 measures voltage and current signalsin the coil to detect the receiver device 150A that is on a chargingsurface of the wireless charging system 100 and provides the voltage andcurrent signals to the microcontroller 130. The microcontroller 130determines how to control the coil for effectively transferring power tothe detected receiver device 150A based on the received signals. Thecoil driving module 135 and the microcontroller 130 operate as a dynamicfeedback system for charging the receiver device 150A. The interactionbetween the coil driving module 135 and the controller 130 is describedin detail below with respect to FIG. 2. Although not shown in FIG. 1,the wireless charging system 100 may include a plurality of coils forwirelessly charging one or more devices. In some embodiments, there maybe a separate coil driving module 135 for each of the plurality ofcoils. In other embodiments, there may be a coil driving module 135 thatcontrols one or more coils.

The USB module 140 includes USB-standard circuits to deliver power to areceiver device 150B using one or more USB cables. In addition towirelessly charging devices, the USB module 140 allows the wirelesscharging system 100 to charge additional devices that may not becompatible with wireless power transfer or when there is a maximumnumber of devices on the charging surface of the wireless power transfermethod. The USB module 140 may include a data line for data transfer,e.g., firmware updated for the wireless charging system 140.

The storage 145 includes a machine-readable medium on which is storedinstructions embodying any one or more of the methodologies or functionsdescribed herein. The instructions (e.g., software) may also reside,completely or at least partially, within a memory in the microcontroller130 or within a cloud and transmitted over a network. The term“machine-readable medium” can include a single medium or multiple media(e.g., a centralized database, or associated caches and servers) able tostore instructions. The term “machine-readable medium” should also betaken to include any medium that is capable of storing instructions forexecution by a machine and can cause the machine to perform any one ormore of the methodologies disclosed herein.

Example Microcontroller and Coil Driving Module

FIG. 2 is a system diagram of a microcontroller 130 and a coil drivingmodule 135 of FIG. 1, in accordance with an example embodiment. AlthoughFIG. 2 focuses on interactions between the microcontroller 130 and thecoil driving module 135, the microcontroller 130 is connected toadditional modules and controls the additional modules as shown inFIG. 1. Additionally, FIG. 2 only shows an interaction between one coildriving module 135 and the microcontroller 130. However, the wirelesscharging system 100 may include an array of coils, and each coil in thearray may be driven by a different coil driving module 135. Theplurality of coil driving modules 135 are controlled by themicrocontroller 130. In alternative embodiments, different and/oradditional components may be included in the microcontroller 130 and/orthe coil driving module 135 and more than one receiver device 150A maybe connected to the coil driving modules 135.

The microcontroller 130 includes a pulse width modulation (PWM)controller system 205, a PWM generator 210, a first analog to digitalconverter (ADC) 215, and a second ADC 220. The microcontroller 130 isconnected to the coil driving module 135 that includes a coil drivecircuit 225, a coil 230, a coil measurement circuit 235, andcommunication demodulation circuit 240. Based on positions of thereceiver devices 150A on the charging surface of the wireless chargingsystem 100, the microcontroller 130 selects a subset of coils 230 tosend driving signals to. The selected subset of coils 230 are suppliedwith a PWM signal to wirelessly charge the receiver devices 150A usinginductive charging. The microcontroller 130 and the coil driving module135 form a feedback control system for selecting a particular subset ofcoils 230 in the wireless charging system 100 and providing signals tothe selected coils 230. In alternative embodiments, the PWM controllersystem 205 and the ADCs (e.g., first ADC 215 and the second ADC 220) maybe external to the microcontroller 130 and are controlled by themicrocontroller 130.

The coil drive circuit 225 receives a PWM waveform from the PWMgenerator 210 and generates a voltage signal for driving the coil 230.The coil measurement circuit 235 measures amplitudes and phases ofvoltage and a current in the coil 230 and the measurements are providedto a first ADC converter 215 of the microcontroller 130 and fed into thePWM control system 205 as an input to a control algorithm thatdetermines how to select a PWM signal to be generated by the PWMgenerator 210.

The coil driving module 135 also includes a communication demodulationcircuit 240 that demodulates signals from the receiver device 150A byanalyzing changes in current running through the coil 230. The currentin the coil 230 is a function of load in the receiver device 150A, andthe load varies based on communication signal. By monitoring the changein current in the coil 230, the communication signal from the receiverdevice 150A can be demodulated. The communication demodulation circuit240 receives the current from the coil 230 for demodulation and thedemodulated signal is sent to the second ADC 220. Once the ADC 220converts the demodulated signal in alternating current (AC) form intodirect current (DC) form, the demodulated signal is provided as an inputto the PWM control system 205 for driving the coils 230 to use incharging the receiver device 150A. In other embodiments, thecommunication demodulation circuit 240 may analyze changes in voltageacross the coil 230 instead of current or in addition to current.

Example Coil Drive Circuit

The coil drive circuit 225 is connected to the PWM generator 210 thatsupplies a PWM waveform to the coil drive circuit 225. Given a targetoperating frequency f_(op), a target RMS voltage amplitude V, and atarget phase θ, the coil drive circuit 225 outputs a voltage waveformVres to the coil 230. The coil drive circuit 225 may be a DC to ACinverter that outputs the sinusoidal voltage waveform Vres used by thecoil 230 for generating power for charging the receiver device 150A. Thecoil drive circuit 225 receives a DC power source Vdd from the powermanagement module 110.

One possible approach for implementing the coil drive circuit 225 is touse a two-stage inverter design. A first stage may be a DC to DCconverter that determines the amplitude V of the voltage waveform Vres,and a second stage may be a DC to AC inverter for controlling thefrequency f_(op). However, this approach requires a complex circuitstructure, which can be expensive for implementing. Instead, simplercircuit structures such as a half-bridge inverter or a full-bridgeinverter may be used instead to reduce the circuit complexity and cost.Despite using simpler circuit structures, the coil drive circuit 225 mayachieve a same range and flexibility of control as using the two-stageinverter design by selecting the appropriate control signals. Thehalf-bridge inverter approach is described below with respect to FIGS.3A and 3B, and the full-bridge inverter approach is described withrespect to FIG. 4.

FIG. 3A is a first example of a coil drive circuit 225, in accordancewith an embodiment. The coil drive circuit 225 includes a half-bridgedriver 360 that controls a first transistor 350A and a second transistor350B. The coil drive circuit 225 may be a half-bridge inverter thatincludes a buffer 330 connected to a first deadtime control circuit 310Athat connects to a gate driver 320. The PWM waveform is passed throughthe buffer 330 and the first deadtime control system 310A and providedto the gate driver 320 as a first input. The coil drive circuit 225 alsoincludes an inverter 340 connected to a second deadtime control system310B that connects to the gate driver 320. The PWM waveform is passedthrough the buffer 330 and the second deadtime control circuit 310B andprovided to the gate driver 320 as a second input. The gate driver 320provides a first gate signal to the first transistor 350A and a secondgate signal to the second transistor 350B.

The PWM waveform is a discrete signal that switches between an on stateand an off state at a frequency f_(pwm), and a proportion of a time thatthe PWM waveform is at the on state and a time that the PWM waveform isat the off state during a period is controlled by a duty cycle η_(pwm).To control the output voltage waveform Vres for driving the coil 230,the frequency f_(pwm), the duty cycle η_(pwm), and the phase φ_(pwm) ofthe PWM waveform that is provided to the coil drive circuit 225 isselected based on target characteristics of the voltage waveform Vres.The target characteristics may include the target operating frequencyf_(op), the target RMS voltage amplitude V, and the target phase θ.

In some embodiments, the frequency of the PWM waveform f_(pwm) is set tobe

f _(PWM) =f _(op)  (Equation 1)

and the duty cycle η_(pwm) of the PWM waveform is set to be

$\begin{matrix}{\eta_{pwm} = {{\frac{1}{\pi}{\arcsin \left( {\frac{\pi}{2} \cdot \frac{V}{Vdd}} \right)}} + {\left( {\tau_{dr} - \tau_{df}} \right)f_{op}}}} & \left( {{Equation}\mspace{14mu} 2} \right)\end{matrix}$

where τ_(dr) is the delay time of the rising edge of the outputwaveform, and τ_(df) is the delay time of the falling edge.

The phase of the center of the PWM waveform φ_(pwm) is set to be thetarget phase θ of Vres, or the phase of the rising edge of the PWMwaveform is set to be

φ_(pwm)=θ+η₁π+2πτ_(dr) f _(op)  (Equation 3)

In some embodiments, when the target frequency f_(op) is high, aduration of turn-on time (e.g., time at which the PWM waveform is at theon state) is too short for the coil control circuit 225 if the frequencyof the PWM waveform f_(pwm) is set to be equal to the target frequencyf_(op). To effectively charge the receiver device 150A, frequency of thePWM waveform f_(pwm) is set to be a fraction of the target frequencyf_(op), such that the frequency of the PWM waveform f_(pwm) is equal tothe target frequency f_(op) divided by an integer n (i.e., the targetfrequency f_(op) is a harmonic frequency of f_(PWM)). Setting thefrequency of the PWM waveform f_(pwm) to be a lower frequency valueincreases the duration of turn-on time and improves the performance ofthe coil control circuit 225 by providing a higher resolution incontrolling the target RMS voltage amplitude V of Vres. Additionally,there are lower switching losses from the first transistor 350A and thesecond transistor 350B.

To determine whether to set the frequency of the PWM waveform to beequal to the target frequency f_(op) or to be equal to a fraction of thetarget frequency, the PWM control system 205 may first calculate theduty cycle η_(pwm) according to Equation 2. The calculated duty cycleη_(pwm) is compared to a predetermined threshold value, and if thecalculated duty cycle η_(pwm) is smaller than the threshold value, thePWM control system 205 determines that the frequency of the PWM waveformf_(pwm) should be a fraction of the target frequency f_(op). Thepredetermined threshold value may be determined by implementationlimitations and other design requirements, for example, the minimumturn-on time of the gate driver 320, or limit on electromagneticradiations as narrow pulses generate higher harmonic components. In someembodiments, the maximum frequency of the target frequency f_(op) may bea second harmonic of the target frequency f_(op).

The target frequency f_(op) is selected to be the n-th harmonic off_(PWM) when the following condition is satisfied:

$\begin{matrix}{\frac{V}{Vdd} \leq \frac{2}{n\pi}} & \left( {{Equation}\mspace{14mu} 4} \right)\end{matrix}$

When f_(op) is the n-th harmonic, such that

$\begin{matrix}{f_{{PWM}_{-}n} = {\frac{1}{n}f_{op}}} & \left( {{Equation}\mspace{14mu} 5} \right)\end{matrix}$

the duty cycle η_(pwm_n) is set to be

$\begin{matrix}{\eta_{{pwm}\_ n} = {{\frac{1}{n\pi}{\arcsin \left( {\frac{n\pi}{2} \cdot \frac{V}{Vdd}} \right)}} + {\left( {\tau_{dr} - \tau_{df}} \right)\frac{f_{op}}{n}}}} & \left( {{Equation}\mspace{14mu} 6} \right)\end{matrix}$

The phase of the center of the PWM waveform f_(pwm_n) is set to be thetarget phase θ of Vres, or the phase of the rising edge of the PWMwaveform f_(pwm_n) is set to be

$\begin{matrix}{\phi_{{pwm}\_ n} = {\theta + {\eta_{{pwm}\_ n}\mspace{11mu} \pi} + {\frac{2\pi}{n}\tau_{dr}f_{op}}}} & \left( {{Equation}\mspace{14mu} 7} \right)\end{matrix}$

When the value of η_(pwm_n) is small, for example, when

$\frac{nV}{V_{dd}}$

is less than 0.4, η_(pwm_n) can be approximated as η_(pwm_n)≈η_(pwm).Otherwise, the approximation does not hold, and to use a high harmonicfrequency as the target frequency f_(op) of Vres to drive the coil 230,the duty cycle η_(pwm) has to be increased. This prevents the targetfrequency from f_(op) from being arbitrarily high.

FIG. 3B is a second example of a coil drive circuit including a loadswitch, in accordance with an embodiment. In the first example discussedwith respect to FIG. 3A, each coil drive circuit 225 drives a singlecoil. However, because the wireless charging system 100 drives a subsetof coils 230 at a given time instead of driving all of the coils 230 atthe same time, a coil drive circuit 225 may configured to drive aplurality of coils 230 using a load switch. The load switch may allowthe coil drive circuit 225 to switch between driving different coils 230connected to the coil drive circuit 225. For example, the wirelesscharging system 100 may include M coils 230, but only N coils 230 may beturned on at any given time, where N<M. Given these conditions, across-bar system may be created between the coil drive circuits 225 andthe coils 230. The load switch may be added to pairs of drivers andcoils, wherever appropriate.

In the wireless charging system 100, there are a plurality of coils 230for charging a plurality of receiver devices 150A. Depending onparameters such as a number of detected receiver devices 150A andpositions of the detected receiver devices 150A, the wireless chargingsystem 100 drives a particular subset of coils 230 for charging thedetected receiver devices 150A. When the plurality of coils 230 arearranged to overlap each other or arranged to be in proximity to eachother within the wireless charging system 100, there can be unwantedinduced current due to cross-talk between neighboring coils, which canlead to lowered efficiency due to undesirable power loss as well asinaccurate communication signals. For example, the wireless chargingsystem 100 may detect a receiver device and select a first coil forcharging the detected device. When the wireless charging system 100drives the first coil, current through the first coil may induce currentin a neighboring second coil that is not intended to be driven forcharging the detected device. In some embodiments, to avoid the unwantedcross-talk, induced current may be suppressed using a load switch thatturns off coils that are not being driven by a coil drive circuit 225.The addition of the load switch can improve efficiency and accuracy incommunication signal detection.

In the second example shown in FIG. 3B, the coil drive circuit 225includes a load switch 370 that drives a first coil 230A and a secondcoil 230B. In some embodiments, the first coil 230A and the second coil230B may be overlapping. In some embodiments, the first coil 230A andthe second coil 230B may be concentric coils with different diameters.Depending on the position of the receiver device 150A on the chargingsurface of the wireless charging system 100, coils of differentdiameters may be selected for charging the receiver device 150A tooptimize power delivery efficiency. In the embodiment shown in FIG. 3B,there are two coils connected to the coil drive circuit 225, but inother embodiments, there may be more than two coils. The half-bridgedriver 360 receives a PWM waveform from the PWM generator 210 andcontrols the first transistor 350A and the second transistor 350B. Theload switch 370 is connected to a node between the first transistor 350Aand the second transistor 350B. The load switch 370 introduces back toback transistors in series between the node and the coils 230A and 230B,which effectively blocks induced current from flowing through a coilthat is not being driven.

The load switch 370 includes a third transistor 372A and a fourthtransistor 372B connected to the first coil 230A and includes a fifthtransistor 372C and a sixth transistor 372D connected to the second coil230B. The third transistor 372A and the fourth transistor 372B connectedto the first coil 230A are in a first branch of the load switch 370, andthe fifth transistor 372C and the sixth transistor 372D connected to thesecond coil 230B are in a second branch parallel to the first branch.The third transistor 372A and the fourth transistor 372B are connectedto a first gate driving signal G1, and the fifth transistor 372C and thesixth transistor 372D are connected to a second gate driving signal G2.Although not shown in FIG. 3B, the first gate driving signal G1 and thesecond gate driving signal G2 may be generated by the microcontroller130 and provided to the respective transistors. The first gate drivingsignal G1 and the second gate driving signal G2 are generated such thatwhen one of the driving signals is on, the other driving signal is off.Although both of the driving signals may be off at the same time, bothof the driving signals cannot be on at the same time.

In some embodiments, the first coil 230A is connected in series with afirst capacitor C_(A), and the combination of the first coil 230A andthe first capacitor C_(A) forms a LC filter. The first coil 230A and thefirst capacitor C_(A) are selected such that the resonant frequency ofthe LC filter is similar to (e.g., within 10% of) or equal to aswitching frequency of the first transistor 350A and the secondtransistor 350B. When the resonant frequency condition is met, an ACcurrent is produced in the first coil 230A and the first capacitorC_(A), and the AC current generates a magnetic field when passingthrough the first coil 230A. Similarly, the second coil 230B may beconnected in series with a second capacitor C_(A), and the combinationof the components may be selected such that their resonant frequency issimilar to or equal to the switching frequency of the first transistor350A and the second transistor 350B.

FIG. 4 is a third example of a coil drive circuit 225, in accordancewith an embodiment. In the third example, the coil drive circuit 225 isa full-bridge inverter that includes a first half-bridge 410 and asecond half-bridge 420. The first half-bridge 410 and the secondhalf-bridge 420 receive a DC power source Vdd from the power managementmodule 110. Although not shown, similar to the second example, the coildrive circuit 225 including the full-bridge inverter may include a loadswitch and be configured to drive more than one coil.

The first half-bridge 410 receives PWM waveform A and the secondhalf-bridge 420 receives PWM waveform B. PWM waveform A and PWM waveformB are generated by the PWM generator 210 based on instructions from thePWM control system 205. The duty cycles of both PWM waveform A and PWMwaveform B may be set to be 50%. PWM waveform A and PWM waveform B mayhave a phase offset of α degrees in between, such that PWM waveform Aleads PWM waveform B by α degree, or vice versa. Across the firsthalf-bridge 410 and the second half-bridge 420, the coil drive circuit225 outputs the voltage waveform Vres.

To control the target operating frequency f_(op), the target amplitudeV, and the target phase θ of the output voltage wave form Vres, thefrequency of PWM waveform A and PWM waveform B may be set to be equal tothe target operating frequency f_(op) according to Equation 1. The phaseoffset of α between PWM waveform A and PWM waveform B is set to

$\begin{matrix}{\alpha = {{2\mspace{11mu} {\arcsin \left( {\frac{\pi}{2\sqrt{2}}\frac{V}{V_{dd}}} \right)}} + {\left( {\tau_{dr} - \tau_{df}} \right)f_{op}}}} & \left( {{Equation}\mspace{14mu} 8} \right)\end{matrix}$

where τ_(dr) is the delay time of the rising edge of the voltagewaveform Vres, and τ_(df) is the delay time of the falling edge of thevoltage waveform Vres. The phase of the rising edge of LH_PWM to be

$\begin{matrix}{\phi_{1} = {\theta + \frac{\alpha}{2} + {2\pi \tau_{dr}f_{op}}}} & \left( {{Equation}\mspace{14mu} 9} \right)\end{matrix}$

FIG. 5 is a flowchart illustrating a process 500 of driving a coil, inaccordance with an example embodiment. The coil is in a wirelesscharging system that provides wireless power transfer to a receiverdevice. To drive the coil, the wireless charging system determines 510target characteristics of a coil driving signal. The wireless chargingsystem selects 520 a frequency and a duty cycle associated with a pulsewidth modulation (PWM) signal based on the target characteristics. Basedon the selected frequency and duty cycle, the wireless charging systemgenerates 530 the PWM signal. The generated PWM signal is provided 540as an input to a half-bridge inverter, the half-bridge inverterconfigured to generate the coil driving signal. The generated coildriving signal is provided 550 to the coil.

Example Feedback System

As shown in FIG. 2, the feedback system between the microcontroller 130and the coil driving module 135 includes two feedback channels. In afirst feedback channel, measurements from the coil measurement circuit235 is provided to the first ADC 215. The first feedback channel isdiscussed in detail with respect to FIGS. 6 and 7. In a second feedbackchannel, communication signal from the receiver device 150A isdetermined by the communication demodulation circuit 240 and provided tothe second ADC 220. The communication signal may be according to acommunication protocol such as the Qi standard. The second feedbackchannel is discussed in detail with respect to FIGS. 8-10. Signals fromthe first ADC 215 and the second ADC 220 are used by the PWM controlsystem 205 to generate a PWM signal in the PWM generator 210 used todrive coils 230 that charge the receiver devices 150A.

Example High-Precision Measurement System

The wireless charging system 100 measures amplitudes and phases ofvoltage across and current going through the coils 230 and uses themeasurements as the first feedback channel. When a receiver device 150Ais placed in close proximity of the coils 230, the receiver device 150Aloads the coils 230 and causes a change in the voltages and currents ofthe coils 230. By monitoring the change in the voltages and the currentsof the coils 230, the wireless charging system 100 can detect and trackthe receiver device 150A. The wireless charging system 100 may makemeasurements of the amplitude and phase of the voltage and current atpredetermined intervals (e.g., every 50 ms) and use the change in themeasurements of the coils 230 to detect the presence of one or morereceiver devices 150A. As described with respect to FIGS. 12-14, themeasurements may be provided as an input to a machine learning algorithmto determine a number of receiver devices 150A, a position of thereceiver devices 150A on the charging surface of the wireless chargingsystem 100, and a subset of coils in the wireless charging system 100 toactivate to charge the detected receiver devices 150A. Once the subsetof coils to activate is determined, the PWM control system 205 maydetermine how to drive the subset of coils such that the detectedreceiver devices 150A may charge the identified receiver devices 150Aefficiently.

To reduce costs of manufacturing the wireless charging system 100, a lowspeed ADC (e.g., the first ADC 215) may be used. However, the AC signalsin the coils 230 may be high speed signals, and the low speed ADC maynot be able to obtain sufficient samples needed to collect accuratemeasurements. When there may not be enough samples per period due toundersampling in the time domain, there is aliasing in the frequencydomain that causes multiple frequency components to overlap on top ofeach other. When there is aliasing, it may be impossible to separate thedifferent frequency components and accurately reconstruct theoverlapping frequency components. However, because the operatingfrequency f_(op) of the coils 230 are known, a digital signal selectionalgorithm may be used to select an ADC sampling speed f_(s) and adiscrete Fourier transform (DFT) size N to avoid collisions of harmonicsignals. This allows the microcontroller 130 to make high-precisionmeasurements of signals in the coils 230 despite limitations in the ADC.

FIG. 6 is an example of a coil measurement circuit 235, in accordancewith an example embodiment. The coil measurement circuit 235 translatesthe input voltage Vin from the coil 230 into an output voltage Vout thatis compatible with the first ADC 215. The coil measurement circuit 235filters, biases, and scales the input voltage Vin for the first ADC 215.The output voltage Vout is then provided as input to the first ADC 215to be sampled.

In some embodiments, the coil measurement circuit 235 includes anoperational amplifier (op-amp) 605 that is connected to the inputvoltage Vin as an inverting input (−) through a first resistor R1. Thecoil measurement circuit 235 includes an active low pass filter that isimplemented by connecting a second resistor R2 and a first capacitor C1in parallel across the inverting input and the output voltage Vout. Thenon-inverting input (+) is connected to ground through a first resistorR1 and connected to a reference voltage Vref through a parallel networkof a second voltage R2 and a first capacitor C1. At the output of theop-amp 605, a third resistor R3 and a second capacitor C2 are connectedin series. The output voltage Vout is measured across the secondcapacitor C2.

The following equation represents the output voltage Vout at frequencyco,

$\begin{matrix}{V_{out} = \frac{\left( {V_{ref} - {\frac{\left( {\frac{1}{R_{2}} + {j\; \omega \; C_{1}}} \right)^{- 1}}{R_{1}}V_{in}}} \right)}{{j\omega C_{2}R_{3}} + 1}} & \left( {{Equation}\mspace{14mu} 10} \right)\end{matrix}$

If ω is far below the cut-off frequency of the low pass filter, theoutput voltage Vout may be approximated as,

$\begin{matrix}{V_{out} \approx {V_{ref} - {\frac{R_{2}}{R_{1}}V_{in}}}} & \left( {{Equation}\mspace{14mu} 11} \right)\end{matrix}$

The coil measurement circuit 235 provides the output voltage Vout to thefirst ADC 215. The first ADC 215 samples the output voltage Vout andconverts the analog signal to a digital signal.

For the following embodiments of the digital signal selection algorithm,the relationship between the sampling frequency f_(s) and the operatingfrequency f_(op) of the coil 230 is defined as

$\begin{matrix}{{\frac{b}{a}\overset{\Delta}{=}\frac{f_{s}}{f_{op}}},{{{where}\mspace{14mu} {\gcd \left( {a,b} \right)}} = 1}} & \left( {{Equation}\mspace{14mu} 12} \right)\end{matrix}$

Because the clock of the first ADC 215 and the clock of the PWM controlsystem 205 used to generate the signal in the coil 230 are from a samecrystal or oscillator driving the microcontroller 130, the relationshipof

$\frac{f_{s}}{f_{op}}$

is a rational number. Then, the DFT size N is selected to be a multipleof b. When the DFT size N is not a multiple of b, the operatingfrequency f_(op) does not have an integer index after performing theDFT. After performing the DFT, the k-th harmonic of the operatingfrequency f_(op) collides with k+b, k+2b, . . . k+nb, where n is aninteger value greater or equal to 1.

In a first embodiment, the sampling frequency f_(s) of the first ADC 215is selected out of all the discrete sampling speed options of the firstADC 215. The sampling frequency f_(s) is defined by:

$\begin{matrix}{f_{s} = {{argmax}\left\{ {{b;{\frac{b}{a}\overset{\Delta}{=}\frac{f_{s}}{f_{op}}}},{{{where}\mspace{14mu} {\gcd \left( {a,b} \right)}} = 1}} \right\}}} & \left( {{Equation}\mspace{14mu} 13} \right)\end{matrix}$

where gcd is a function representing the greatest common divisor of twointegers.

By choosing the sampling frequency f_(s) according to Equation 13, theoperating frequency f_(op) of the coil 230 collides with harmonics withindices as large as possible with intensities as small as possible. Thisresults in minimal distortion to the operating frequency f_(op).

After selecting the sampling frequency f_(s), a DFT size of N isselected to be the biggest multiple of b that is allowed by memory sizeand computational power of the microcontroller 130 used for performingthe DFT. Based on the selected DFT size N, the first ADC 215 samples theoutput voltage Vout and collects N samples {a₀, a₁, . . . , a_(N-1)}.

The Fourier value c is determined by performing DFT on the N samples{a₀, a₁, . . . , a_(N-1)}:

$\begin{matrix}{c = {\sum\limits_{i = 0}^{N - 1}{a_{i}e^{- \frac{i2\pi ia}{b}}}}} & \left( {{Equation}\mspace{14mu} 14} \right)\end{matrix}$

The RMS amplitude and phase of the output voltage Vout are calculated:

V _(RMS)=√{square root over (2)}|c|  (Equation 15)

θ=∠c  (Equation 16)

The first embodiment discussed above requires the DFT size N to be amultiple of b, which can be impractical as b can be a large value thatexceeds a maximum DFT size limited by memory size and computationalpower of the microcontroller 130.

In a second embodiment of the digital signal selection algorithm, theDFT size N is selected to be less than b. However, when the DFT size Nis less than b, the digital signal selection algorithm is sensitive towindowing effect and can result in spectral leakage. Therefore, the DFTsize N is selected to be less than a maximum DFT size N_(max) of thefirst ADC 215 while minimizing the windowing effect.

First, a frequency index k is defined by:

$\begin{matrix}{k = \frac{aN}{b}} & \left( {{Equation}\mspace{14mu} 18} \right)\end{matrix}$

The frequency index k may be an integer or a non-integer.

When the frequency index k is a non-integer value, the frequencyspectrum is convolved with a sin c function. The sin c function is zeroat each integer point and reaches local maxima at halfway betweenadjacent integers (e.g., an integer plus 0.5), and to minimize windowingeffect when performing the DFT, the fractional part of k k_(frac) needsto be minimized. The fractional part of k k_(frac) is defined by:

$\begin{matrix}{k_{frac} = \left\{ \begin{matrix}{{k - \left\lfloor k \right\rfloor},} & {{{{if}\mspace{14mu} k} - \left\lfloor k \right\rfloor} \leq 0.5} \\{{\left\lceil k \right\rceil - k},} & {{{{if}\mspace{14mu} \left\lceil k \right\rceil} - k} < 0.5}\end{matrix} \right.} & \left( {{Equation}\mspace{14mu} 19} \right)\end{matrix}$

The smallest k_(frac) of

$\frac{1}{b}$

is achieved when

aN≡1(mod b)

and the second smallest k_(frac) of

$\frac{2}{b}$

is achieved when

aN≡2(mod b)

and the i-th smallest kfrac of

$\frac{i}{b}$

is achieved when

aN≡i(mod b)

Therefore, the DFT size N that is less than the maximum DFT size N_(max)is selected to minimize k_(frac). Given the DFT size N, the samplingfrequency f_(s) is selected from all discrete sampling speed optionsbased on the following:

$\begin{matrix}{f_{s} = {{argmax}\left\{ {{\frac{b}{\gcd \left( {a,{\gcd \left( {N,b} \right)}} \right)};{\frac{b}{a}\overset{\Delta}{=}\frac{f_{s}}{f_{op}}}},{{{where}\mspace{14mu} {\gcd \left( {a,b} \right)}} = 1}} \right\}}} & \left( {{Equation}\mspace{14mu} 20} \right)\end{matrix}$

The first ADC 215 is used to perform a sampling of the output voltageVout and collect N samples {a₀, a₁, . . . , a_(N-1)}. The Fourier valuec, the RMS amplitude V_(RMS), and the phase θ are determined based onEquations 14, 15, and 16, respectively.

In a third embodiment, an ADC parameter A is calculated for selectingthe sampling frequency f_(s) of the first ADC 215. For each possiblesampling frequency f_(s) of the first ADC 215, the following isdetermined:

$\begin{matrix}{{\frac{b}{a}\overset{\Delta}{=}\frac{f_{s}}{f_{op}}},{{{where}\mspace{14mu} {\gcd \left( {a,b} \right)}} = 1}} & \left( {{Equation}\mspace{14mu} 12} \right)\end{matrix}$

If b is less than maximum DFT size N_(max), the DFT size N is set to

N=N _(max)−(N _(max) mod b)  (Equation 21)

Otherwise, if b is greater or equal to the maximum DFT size N_(max), theDFT size N is calculated by determining the inverse of a modulo b.First, the value of N₁ is determined by:

N ₁ =a ⁻¹ mod b  (Equation 22)

Starting with integer i=1, iterations of the following is performed byincrementing i.

N _(i) =iN ₁ mod b  (Equation 23)

If N_(i)<N_(max), the DFT size N is set to N_(max), and the loop isbroken. Otherwise, i is incremented, and the N_(i) is recalculated forthe new i value. Based on the determined N, the ADC parameter A iscalculated by:

$\begin{matrix}{A = \frac{b}{gc{d\left( {a,{\gcd \left( {N,b} \right)}} \right)}}} & \left( {{Equation}\mspace{14mu} 24} \right)\end{matrix}$

The operating frequency f_(op) collides with harmonics 1+A, 1+2A, 1+3A .. . . The sampling frequency f_(s) is determined such that A ismaximized from all possible ADC parameter A calculated above. Afterselecting the sampling frequency f_(s), a discrete Fourier transform(DFT) size of N is selected to be the biggest multiple of b that isallowed. Based on the selected DFT size N, the first ADC 215 samples theoutput voltage Vout and collects N samples {a₀, a₁, . . . , a_(N-1)}.The Fourier value c, the RMS amplitude V_(RMS), and the phase θ aredetermined based on Equations 14, 15, and 16, respectively.

FIG. 7 is a flowchart illustrating a process of performing digitalprocessing on samples of a signal from a coil, in accordance with anembodiment. A wireless charging system measures an amplitude and a phaseof a signal of a coil driven at an operating frequency. The wirelesscharging system selects 710 a first integer value and a second integervalue, where the first integer value and the second integer value arecoprime integers. Based on the first integer value and the secondinteger value, the wireless charging system determines 720 a ratiobetween the first integer value and the second integer value. Thewireless charging system selects 730 a sampling frequency for samplingthe signal, where a ratio between the sampling frequency and theoperating frequency is same as the ratio between the first integer valueand the second integer value. After selecting the sampling frequency,the wireless charging system samples 740 the signal at the selectedsampling frequency.

Example Communication Signal Demodulation System

The wireless charging system 100 demodulates communication signals fromthe receiver device 150A using the communication demodulation circuit240. In some embodiments, the receiver device 150A communicates with thewireless charging system 100 according to Qi communication protocol. Thecommunication demodulation circuit 240 allows the wireless chargingsystem 100 to demodulate the communication signals despite noisyconditions and interferences from multiple receiver devices 150A beingconnected to the wireless charging system 100. Because the wirelesscharging system 100 may charge multiple receiver devices at the sametime, accurate communication signal detection for each of the receiverdevices is important for effectively charging the receiver devices 150A.The communication signal may encode characteristics of the receiverdevices such as a state of charge in a battery, power required tosuccessfully charge the receiver device, amount of power being receivedat the receiver device, erroneous state of the receiver, and cellvoltage of the battery. The communication signal is provided to the PWMcontrol system 205 as a feedback channel such that the PWM controlsystem 205 may drive the coils 230 for charging the receiver devices150A.

FIG. 8 is an example encoding of a communication signal in a receiverdevice, in accordance with an example embodiment. The receiver device150A includes a switch that changes the load of the receiver device 150Adepending on which state the switch is at (e.g., ON state or OFF state).Since the current in the coil 230 of the wireless charging system 100 isa function of the load of the receiver device 150A, the switch state ofthe receiver device 150A may be determined by analyzing the current inthe coil 230. Communication signal can be transmitted by the receiverdevice 150A by encoding a message into a sequence of ON/OFF patternsusing the switch. From the wireless charging system 100, thecommunication signal can be decoded by determining how the current inthe coil 230 changes and mapping the changes to ON/OFF patterns.

The Qi communication protocol involves encoding zeros and ones using thestate of the switch. Each clock period corresponds to a bit, and anumber of transitions in the switch state during a clock periodindicates the value of the bit. When there is one transition during aclock period, a bit corresponding to the clock period is encoded with avalue of zero. Alternatively, when there are two transitions during theclock period, the bit is encoded with a value of one.

The activity in the receiver device 150A is synchronized according to aclock signal. The clock signal oscillates between a high state and a lowstate during each clock period. In some embodiments, each clock periodcorresponds to a duration of 0.5 ms. In other example embodiments, eachclock period corresponds to a different time duration. The clock signalmay be a square wave with a 50% duty cycle such that the clock signal isat the high state during 50% of a duration of each clock period.

The receiver device 150A encodes a plurality of bits into acommunication signal that is synchronized with the clock signal. Thereceiver device 150A varies the state of the load switch between the ONstate and the OFF state for encoding the bits. For example, during clockperiod A, the communication signal changes from the OFF state to the ONstate at the beginning of the clock period and changes from the ON stateto the OFF state at the middle of the clock period. Therefore, duringclock period A, there is a total of two transitions, and the bitcorresponding to the clock period A is encoded with a value of 1. Duringclock period B, the communication signal changes from the OFF state tothe ON state at the beginning of the clock period and does not changeduring a remaining duration of the clock period. Since there is only onetransition during clock period B, the bit corresponding to the clockperiod B is encoded with a value of 0. During clock period C, thecommunication signal changes from the ON state to the OFF state at thebeginning of the clock period and changes from the OFF state to the ONstate at the middle of the clock period. Since there are twotransitions, the bit corresponding to the clock period C is encoded witha value of 1. The receiver device encodes the bits for each of thesubsequent clock periods (e.g., clock periods D, E, F, and so on)according to the example encoding scheme described above.

FIG. 9 is a block diagram of a circuit for demodulating a signal from areceiver device 150A, in accordance with an embodiment. The receiverdevice 150A communicates with the wireless charging system 100 per Qicommunication specification. Typical Qi communication demodulationmethods rely on a charger with a fixed location for placing a receiverdevice such that the relative location between a pair of receiver deviceand a coil does not vary. Given the fixed location, a transfer functionspecific to the fixed location is applied to the received communicationsignal for decoding. However, the wireless charging system 100 allowscharging of multiple receiver devices 150A which can cause communicationsignal distortion due to the different communication signals overlappingwith each other. Additionally, the wireless charging system 100 allowsthe receiver devices 150A to be placed freely within a charging surfacewhich can lead to poor alignment between the receiver devices 150A andthe coils 130. Therefore, using typical Qi communication demodulationmethods to decode the communication signals can result in inaccurateresults.

The communication demodulation circuit 240 receives a coil current fromthe coil 230 that is coupled to the receiver device 150A. Thecommunication demodulation circuit 240 demodulates the communicationsignal transmitted by the receiver device 150A from the coil current.Once the communication signal is demodulated, the communication signalmay be used by the microcontroller 130 for charging the receiver device150A. In some embodiments, the communication demodulation circuit 240includes an initial stage scaling module 910, a peak detection andrectification module 920, a multi-stage scaling and low pass filtermodule 930, a compactor module 940, an integrator 950, and a controller960.

The coil current includes two waves: a power supply wave for providingcharging current to the receiver device 150A and a carrier waveincluding the Qi communication signal from the receiver device 150A.Because the carrier wave portion of the coil current carries thecommunication signal, it is useful to isolate the communication signalsfor communication demodulation. The power supply wave is significantlygreater in amplitude compared to the carrier wave, and the communicationdemodulation circuit 240 performs a scaling operation separately for thepower supply wave and the carrier wave. The communication demodulationcircuit 240 may scale the power supply wave first using the initialstage scaling module 910 and pass the resulting signal to the peakdetection and rectification module 920 to remove the power supply waveportion from the coil current such that further stages in thecommunication demodulation circuit 240 may focus on the carrier waveportion carrying the communication signal.

The communication demodulation circuit 240 may find the signal envelopeat 2 kHz to recover the communication signal since the frequency of thecommunication signal from the receiver device 150A carrier wave is 2kHz. After determining the envelope, the communication demodulationcircuit 240 filters and scales the signal before passing the signalthrough a comparator to digitize the signal into a high state or a lowstate. Once the digital signal is determined, number of transitionsduring each of the clock periods can be determined to determine thecommunication signal.

The communication demodulation circuit 240 passes the coil currentthrough the stage scaling module 910 that scales the amplitude of thecoil current to be within a predetermined range. In particular, thestage scaling module 910 may scale the amplitude of the coil current tobe appropriate for functions of the peak detection and rectificationmodule 920. The stage scaling module 910 may use a differential circuitto adjust the midpoint of the coil current and the amplitude of the coilcurrent. The gain used by the stage scaling module 910 is provided bythe controller 960.

Once the stage scaling module 910 scales the coil current, the peakdetection and rectification module 920 identifies peaks in the coilcurrent and rectifies the coil current. The hysteresis of the peakdetection and rectification module 920 is set such that the power supplywave is removed from the coil current and the carrier wave that carriesthe communication signals remains. After rectifying the wave in the coilcurrent, the peak detection and rectification module 920 may filter outthe DC bias to ensure that the signal is AC coupled.

The rectified coil current is then passed to a multi-stage scaling andlow pass filter module 930. The multi-stage scaling and low pass filtermodule 930 further scales the coil current that was scaled by theinitial stage scaling module 910. The coil signal that is passed to themulti-stage scaling and low pass filter module 930 is representative ofthe carrier wave, and the multi-stage scaling and low pass filter module930 scales the carrier wave portion of the coil signal. Each of thescaling stages may have a configurable gain set by the controller 960.Because the amplitude of the coil is dynamic, it is difficult to selecta fixed-gain without the risk of either saturating the op-amp in theinitial stage scaling module 910 or the multi-stage scaling and low passfilter module 930 by exceeding its limits or missing small amplitudes.Therefore, instead of using a fixed-gain, the gain is dynamicallydetermined by the controller 960. The rectified coil current is alsopassed to the integrator 950 that determines an average amplitude of thecoil current. The average amplitude of the coil current is used as aninput by the controller 960 that determines a gain for the stage scalingmodule 910 and the different stages in the multi-stage scaling and lowpass filter module 930.

The multi-stage scaling and low pass filter module 930 also passes thecoil current through a low pass filter to filter out high frequencysignals above a threshold frequency to extract the communication signalfrom the coil current. In the coil current, the power supply wave mayhave a higher frequency compared to the carrier wave carrying thecommunication signal. For example, the power supply wave may correspondto a frequency of 100-150 kHz that is greater than the frequency of thecommunication signal at 2 kHz. The power supply wave gets filtered outby the low pass filter with a cut-off frequency of 10 kHz and themulti-stage scaling and low pass filter module 930 outputs a signal thatrepresents just the communication signal generated by the receiverdevice 150A.

The comparator module 940 compares the signal output from themulti-stage scaling and low pass filter module 930 to a comparison valueto digitize the communication signal included in the coil current. Thecomparator module 940 determines when the amplitude of the signal isbelow or equal to a comparison value and assigns a value of zero thatrepresents a low state and when the amplitude of the signal is greaterthan the comparison value assigns a value of one that represents a highstate. In some embodiments, the functions of the comparator module 940may be performed by the second ADC 220 of the microcontroller 130, andthe communication demodulation circuit 240 does not include thecomparator module 940.

Example for Error Correction

In a conventional Qi standard signal processing procedure, a number oftransition is determined for each clock period to determine a bit valueof either a zero or a one. A conventional method for addressing errorsin communication systems is to use an error correction code. However,because there is no such error correction code in Qi communicationprotocol, if there is an error in the decoding attempt while decoding apacket from a receiver device 150A using a typical Qi communicationdemodulation methods, the decoding of the packet fails and the packet isunrecoverable.

In some example embodiments, a parity bit may be added at the end of abyte (e.g., 8 bits) of communication signals by a receiver device 150A,to ensure that the byte has an odd number of l's. When a packetincluding a plurality is transmitted by the receiver device 150A to thewireless charging device 100, there is a checksum at the end of eachpacket that is a bit-wise XOR of all the bytes in the packet. At thebeginning of a packet, there is a header byte that identifies a type ofpacket. There is a finite selection of possible header bytes, and eachheader byte corresponds to a different type of packet.

The communication demodulation circuit 240 analyzes the coil current inthe coil 230 and determines whether the communication signal from thereceiver device 150A is at a low state or a high state at a given time.The communication signal is provided to the PWM control system 205 fordecoding after passing through the communication demodulation circuit240 and the second ADC 220. However, because of faulty hardware in thewireless charging system 100, noise in the wireless communicationchannel between the receiver device 150A and the wireless chargingsystem 100, or interference between multiple receiver devices on thewireless charging system 100, spurious transitions may be introducedinto the signal. To avoid being unable to recover packets, themicrocontroller 130 may perform may perform error correction whendecoding the communication signal from the signal output from thecommunication demodulation circuit 240.

In some embodiments, the spurious transitions can be detected when themicrocontroller 130 decodes the bits in the transmission packets. Whenthere are more than two transitions (e.g., the maximum number accordingto Qi protocol) in a single clock period, it means that there must bespurious transitions due to noise and interference. Therefore, errorcorrection is required to remove the effects of the spurioustransitions. If there are more than two transitions detected, an evennumber of transitions with a spacing of less than a threshold durationis removed. The threshold duration may be selected by observing spacingsof spurious transitions and set to maximize error correction accuracywithout introducing false positives. After removing the even number oftransitions with spacing of less than a threshold duration, thecorresponding bit is decoded with a value of 0 if there is onetransition remaining and the corresponding bit is decoded with a valueof 1 if there are two transitions remaining.

In some embodiments, the bit correction method may fail if even afterremoving an even number of transitions with a spacing of less than athreshold value, there is a number of transitions greater than 1. Foreach clock period in which the bit correction method fails, itscorresponding bit is flagged as undecodable. After flagging a bit asbeing undecodable, the microcontroller 130 continues to decodesubsequent bits that can be decoded and flag the bits that areundecodable.

After applying the decoding algorithm, there is a sequence of 0's, l's,and undecodable bits for a packet, where the packet includes one or morebytes. An error correction algorithm may be applied to the sequence ofdecoded bits. The error correction algorithm may first use parity bitsfor recovering one or more undecodable bits at the byte level. Asdiscussed above, there may be a parity bit at the end of each byte toensure that there is an odd number of l's in the byte. The errorcorrection algorithm may recover as many undecodable bits as possibleusing the parity bit within a byte. For example, in a particular byte,if only one bit is flagged as being undecodable, the undecodable bit maybe recovered using the parity bit. However, if there is more than onebit that is undecodable in a byte, the undecodable bits cannot berecovered using the parity bit. In this case, the undecodable bit isrecovered at the packet level.

Each bit B (undecodable and decodable) corresponds to a byte index(e.g., i) within a packet and a bit index (e.g., j) within the byte. Abit B at the j-th bit of the i-th byte may be denoted as B_(ij).Positions of a first bit may be denoted as (i₁, j₁), a second bit as(i₂, j₂), a third bit as (i₃, j₃) and so forth such that the position ofan m-th bit is denoted as (i_(m), j_(m)). Since there are N bytes in apacket, i may be 0, 1, 2, . . . , N−1. In each byte there are 8 bits, soj may be 0, 1, 2, . . . , 7. For each byte in a packet, there is aparity bit: P₀, P₁, P₂ . . . P_(N-1). There is also a checksum byte inthe packet that represents a result of bit-wise XOR of all of the bytesin the packet such that the checksum byte includes a bit for each indexC₀, C₁, C₂ . . . C₇.

In some embodiments, some undecodable bits may recovered at the packetlevel using the checksum byte. As long as a pair of undecodable bits at(i_(a), j_(a)) and (i_(b), j_(b)) satisfy the condition of j_(a)≠j_(b),the undecodable bits may be recovered. That is, if the undecodable bitsdo not have the same bit index j within its respective byte, the bitsmay be decoded according to the following algorithm. For eachundecodable bit at (i_(a), j_(a)), the bit B_(ia jb) is set to

B _(ia jb)=Σ_(i≠i) _(a) B _(i ja) ⊕C _(ja)  (Equation 25)

Once all of the undecodable bits that can be recovered is set to avalue, the parity bit test and the checksum byte tests are performed. Ifall of the bits are consistent according to these tests, the PWM controlsystem 205 determines that decoding has succeeded. If there is only onechecksum bit C₃ and one parity bit P₁ that are inconsistent, the bitB_(ij) is inverted (e.g., 0 to 1 or 1 to 0). If there are more than onechecksum error and one parity bit error, the decoding algorithm fails.When the decoding algorithm fails, the corresponding packet may bedropped.

FIG. 10 is a flowchart illustrating a process of demodulating a signalfrom a receiver device, in accordance with an example embodiment. Thewireless charging system receives 1010 the signal from the receivedevice using a coil. The wireless charging system applies 1020 a firstgain to the signal. Responsive to applying the first gain, the wirelesscharging system performs 1030 a rectification on the signal. After thesignal is rectified, the wireless charging system applies 1040 a secondgain to the rectified signal. Responsive to applying the second gain,the wireless charging system compares 1050 the signal to a predeterminedvalue to determine whether the signal is at a high level or at a lowlevel. The wireless charging system determines 1060 a byterepresentation of the current signal based on the comparison. Thewireless charging system transmits 1070 the byte to a controller of thewireless charging system configured to drive the coil for charging thereceiver device.

Receiver Device Detection and Coil Selection

FIG. 11 is an example layout 1100 of multiple coils in a wirelesscharging system, in accordance with an embodiment. In the example layout1100, there are four overlapping coils that can be activated to chargemultiple receiver devices 150A. In the example shown in FIG. 11, thereare four coils, a first coil 1110, a second coil 1120, a third coil1130, and a fourth coil 1140, that may be arranged in a horizontalplane. The layout 1100 can charge two receiver devices 150Asimultaneously by activating different subsets of the coils depending onthe positions of the receiver devices 150A. In other embodiments, theremay be fewer or additional coils in the array of coils, relativeposition of overlapping coils may be different, size of the coils mayvary. Based on the configuration of the coils in the wireless chargingsystem, the wireless charging system may charge a different number ofreceiver devices 150A at a given time.

In some embodiments, each of the first coil 1110, the second coil 1120,the third coil 1130, and the fourth coil 1140 has an outer radius R1.The outer radius R1 of the coils may be selected to be large enough tocharge receiver devices 150A within a threshold distance from thesurface of the wireless charging system 100, but not so large that themetallic components of the receiver devices 150A become overheatedduring charging due to eddy currents.

Each of the first coil 1110, the second coil 1120, the third coil 1130,and the fourth coil 1140 has an inner radius R2 that is smaller than theouter radius R1. The inner radius R2 is selected such that it is largeenough to ensure sufficiently large quality factor of the coils yetsmall enough such that there are enough loops in the coils to createsufficient field at the receiver devices 150A for charging efficiently.

In some embodiments, the first coil 1110, the second coil 1120, thethird coil 1130, and the fourth coil 1140 are made of Litz wire withenough strands to mitigate loss due to skin effects and proximityeffects and enough aggregate cross-sectional area to carry drivingcurrent during charging. However, the wires cannot be too thick becauseit can reduce the number of loops in the coils and cause weaker field atthe receiver devices 150A. For each of the coils, the leads of the coilsmay be twisted with each other, which could reduce noise due toelectromagnetic interference.

In some embodiments, a relative spacing between two adjacent coils isequal to the outer radius R1. For example, as shown in FIG. 11, thedistance between an outermost loop of the first coil 1110 and anoutermost loop of the second coil 1120 is the same as the outer radiusR1. When the spacing between two adjacent coils is equal to the outerradius R1, the field at the intersection of the two coils is strongenough to deliver designated power to a receiver device 150A when thereceiver device 150A is positioned at the intersection. If two adjacentcoils are disposed farther apart such that the relative spacing isgreater than the outer radius R1, there can be a region on the chargingsurface of the wireless charging system 100 with a lower field intensitythan what is required for charging the receiver device 150A.Additionally, when two adjacent coils are spaced apart at a distanceequal to the outer radius R1, mutual coupling between adjacent coils canbe minimized.

Resonant frequencies of the coils are chosen such that two closest coilsthat can be turned on simultaneously during charging have differentresonant frequencies that are far apart and not harmonic frequencies ofeach other. This reduces mutual coupling (or cross-talk) between thecoils, and even if there were residual mutual coupling, the effect ofthe mutual coupling is reduced.

In a typical way of identifying a receiver device 150A, a wirelesscharging system monitors current in a coil and determines that there isa receiver device on the wireless charging system once a change in thecurrent is greater than a predefined threshold. More specifically, thewireless charging system may monitor one or more of current amplitude,current phase, offset of system resonant frequency, and quality factorand detect the receiver device based on change in the one or morefactors. Responsive to determining that the change in the current isgreater than the predefined threshold, the wireless charging systemassociates the coil to the detected receiver device.

However, this approach can have drawbacks in a wireless charging systemwith multiple coils. Since the multiple coils are coupled to each other,when a receiver device is placed on the wireless charging system, coilsmay erroneously be associated with the receiver device due to couplingwith the coil that is most effective for power delivery to the receiverdevice. Activating incorrect subsets of coils can lead to lower chargingefficiency and reliability in charging the receiver device.Additionally, it is difficult to determine a threshold value that isindicative of a receiver device given many factors that can affect thethresholds such as brand of the receiver device, model of the receiverdevice, battery level, distance between surface of the wireless chargingsystem and the receiver device (e.g., due to thickness of protectivereceiver device cases or attachments to back of receiver device), andposition of the receiver device with respect to the coils.

To avoid the threshold determination challenges, a supervised machinelearning model may be used by the wireless charging system 100 to detectone or more receiver devices 150A and select a subset of coils forcharging the devices based on the detection.

FIG. 12 is a block diagram of a pulse width modulation (PWM) controlsystem, in accordance with an example embodiment. The PWM control system205 includes a receiver detection module 1210, a training module 1220, acoil selection module 1230, a database of training data sets 1240, and adatabase of computer models 1250. In some embodiments, functionalitiesof one or more of the modules in the PWM control system 205 may beperformed in a data cloud computing configuration or on a localizedcomputer system configurations.

The receiver detection module 1210 receives signals from the coilmeasurement circuit 235 and signals from the communication demodulationcircuit 240 and applies the trained computer models 1250 from thetraining module 1220 to the received signals to identify presence ofreceiver devices 150A.

In some embodiments, the receiver detection module 1210 uses a linearclassifier such as a perceptron for each coil in the wireless chargingsystem 100. The receive detection module 1210 receives an input datavector for each coil that is representative of a state of the coil. Foreach coil, a binary class is defined to determine whether a receiverdevice 150A is present on the wireless charging system 100 and the coilshould be activated to charge the receiver device 150A or no receiverdevice 150A is present. The input data vectors provided to theclassifier may be two dimensional vectors including a first dimensionindicating a change in amplitude of current through the coil and asecond dimension indicating a change in phase. The input data vectorsmay include other features such as voltage or may be represented inother ways. Both dimensions may be a signed (e.g., positive or negative)value. The output is a binary class where a first class indicates that areceiver device 150A is present on the wireless charging system 100 andthe coil should be activated to charge the receiver device 150A and asecond class indicates that a receiver device 150A is not present.

In some embodiments, the receiver detection module 1210 uses anon-linear classifier such as a support vector machine (SVM) for eachcoil in the wireless charging system 100. Similar to the linearclassifier discussed above, for each coil, a binary class may be definedsuch that a first class corresponds to a receiver present on thewireless charging system 100 to be charged by the coil and a secondclass corresponds to no receiver present on the wireless charging system100. The data vectors provided to the classifier may be two dimensionalvectors. A first dimension may be a change in amplitude of currentthrough the coil represented as a percentage and a second dimension maybe a change in phase in degrees. Both dimensions may be a signed (e.g.,positive or negative) value. The output is a binary class where a firstclass indicates that a receiver device 150A is present on the wirelesscharging system 100 and the coil should be activated to charge thereceiver device 150A and a second class indicates that a receiver device150A is not present.

In some embodiments, the receiver detection module 1210 uses anon-linear classifier such as a SVM for multiple coils. In comparison tohaving a different classifier for each of the multiple coils in thewireless charging system 100 and making a decision to activate the coilson a per-coil basis, a multi-coil classifier captures coupling betweenpairs of coils. This allows the wireless charging system 100 to considerthe coils as a whole and select a subset of the coils using a morerobust method compared to considering the coils individually andactivating each of the coils that are identified by the individualclassifiers.

In some embodiments, the wireless charging system 100 may be able tocharge a maximum of two receiver devices 150A at the same time. In thiscase, the multi-coil classifier may be configured to identify aplurality of class types such as:

-   -   No receiver device detected    -   No previously detected receiver device and one new receiver        device detected    -   One previously detected receiver device and one new receiver        device detected    -   Two new receiver devices detected at the same time        In other embodiments, the wireless charging system 100 may be        able to charge a greater number of receiver devices 150A and the        multi-coil classifier has additional classes.

Each type of class may contain multiple classes that corresponds anumber of receiver devices, position of the receiver devices, and whenthe receiver devices are brought onto the wireless charging system 100.For example, for a wireless charging system 100 that includes four coils(coil 1, coil 2, coil 3, and coil 4) that can charge a maximum of twodevices with a constraints that adjacent coils cannot be activated atthe same time has fourteen classes:

Class Description 1 No receiver device 2 A new receiver device detectedon coil 1 3 A new receiver device detected on coil 2 4 A new receiverdevice detected on coil 3 5 A new receiver device detected on coil 4 6 Anew receiver device detected on coil 1 and a new receiver devicedetected on coil 3 7 A new receiver device detected on coil 1 and a newreceiver device detected on coil 4 8 A new receiver device detected oncoil 2 and a new receiver device detected on coil 4 9 A previouslydetectected device on coil 1 and a new receiver device detected on coil3 10 A previously detectected device on coil 1 and a new receiver devicedetected on coil 4 11 A previously detectected device on coil 2 and anew receiver device detected on coil 4 12 A previously detectecteddevice on coil 3 and a new receiver device detected on coil 1 13 Apreviously detectected device on coil 4 and a new receiver devicedetected on coil 1 14 A previously detectected device on coil 4 and anew receiver device detected on coil 2

In some embodiments, the input data vector provided to the receiverdetection module 1210 is a concatenation of data vectors from each ofthe plurality of coils in the wireless charging system 100. For eachcoil, a data vector may include a first dimension that represents achange in amplitude of current through the coil represented as apercentage and a second dimension that represents a change in phase indegrees. For example, the concatenated data vector for the example withfour coils has eight dimensions: change in current amplitude for coil 1,change in current phase for coil 1, change in current amplitude for coil2, change in current phase for coil 2, change in current amplitude forcoil 3, change in current phase for coil 3, change in current amplitudefor coil 4, and change in current phase for coil 4. For coils that arealready associated with a previously detected device, the datacorresponding to these coils may automatically set to 0.

The training module 1220 trains the computer models 1250 using thetraining data sets 1240. The training data sets 1240 include pairs ofinput data vector and desired output of charging configuration. Duringthe training process, the training module 1220 repeatedly updates a setof parameters for the computer models 1250 based on the provided pairsof input data vector and desired charging configuration. The trainingdata sets 1240 may be labeled or annotated by human operators.

During training, the training module 1220 performs iterations ofapplying the computer models 1250 to a pair of input data vector anddesired charging configuration. Based on the computer models 1250, thetraining module 1220 determines an estimated charging configuration. Thetraining module 1220 determines a difference between the estimatedcharging configuration and the desired charging configuration associatedwith the input data vector and updates the set of parameters of thecomputer models 1250 to reduce the difference.

The coil selection module 1230 selects one or more coils to activate tocharge receiver devices detected by the receiver detection module 1210.After the receiver detection module 1210 determines the class, the coilselection module 1230 uses the identified class to determine whichsubset of the coils to drive for charging the detected one or moredevices. The PWM control system 205 may use the subset information incombination with demodulated communication signal from the second ADC220 to drive the subset of the coils.

FIG. 13 illustrates an example process of deploying a classificationmodel for receiver device detection, in accordance with an embodiment.The example process shown in FIG. 13 corresponds to an embodiment inwhich a classifier used by the receiver detection module 1210 is amulti-coil classifier that determines a class based on states of all ofthe coils in the wireless charging system 100. The receiver detectionmodule 1210 receives an input data vector that represents states of allof the coils (e.g., coil 1, coil 2 . . . coil n) in the wirelesscharging system 100. In some embodiments, each coil corresponds to adata vector that includes two dimensions: change in amplitude of currentthrough the coil and change in phase of current through the coil. Thechange in amplitude and the change in phase may be represented aspercentages, absolute values, signed values, and such. Each coil maycorrespond to additional or different types of characteristics such aschange in amplitude of voltage across a coil, change in phase inamplitude of voltage across a coil, and such.

For the multi-coil classifier, the input data vector may be a singlevector that is a concatenation of all of the data vectors for all of thecoils. The receiver detection module 1210 retrieves and applies computermodels 1250 to classify the input data vector into a class (e.g., class3). In one example, class 3 may correspond to a case in which a newreceiver device detected on coil 2. Using the identified class, the coilselection module 1230 may select coil 2 to be activated for charging thenewly detected receiver device.

In other embodiments, the receiver detection module 1210 may use aplurality of classifiers, each classifier corresponding to a coil. Thereceive detection module 1210 may receive a plurality of data vectorswhere each data vector is an input to one classifier with a binary classsuch as a perceptron or a SVM. The receiver detection module 1210 mayoutput a class for each coil such that if there are n coils in thewireless charging system 100, the receiver detection module 1210identifies n classes that each corresponds to a different coil. Based onthe class, the coil selection module 1230 determines whether to activatethe coils on a per-coil basis.

FIG. 14 illustrate a flowchart illustrating a process of training amachine-learned model, in accordance with an embodiment. Themachine-learned model is configured to detect one or more receiverdevices on a charging surface of a wireless charging system and output asubset from a plurality of coils in the wireless charging system forcharging the one or more receiver devices. A computer obtains 1410 atraining data set of desired charging configurations, the training dataset includes a plurality of input data vectors associated with signalsfrom the plurality of coils of the wireless charging system and acorresponding plurality of desired charging configuration that includessubsets of coils to be activated. The computer trains 1420 a set ofparameters of the machine-learned model using the training data set ofdesired charging configurations. During an iteration of the trainingprocess, the computer determines 1430 an estimated chargingconfiguration by applying the machine-learned model with a set ofparameters to an input data vector from the training data set. Based onthe estimated charging configuration, the computer determines 1440 adifference between the estimated charging configuration and the desiredcharging configuration associated with the input data vector. Thecomputer updates 1450 the set of parameters of the machine-learned modelto reduce the difference.

ADDITIONAL CONFIGURATION CONSIDERATIONS

In an embodiment, a wireless charging system may use a simple circuitstructure such as a half-bridge inverter or a full-bridge inverter in acoil drive circuit for driving a coil. The simple circuit structure inthe coil drive circuit reduces circuit complexity and cost of thewireless charging system. Despite using a simple circuit structure, thewireless charging system may achieve a wide range and flexibility ingenerating coil drive signals by selecting the appropriate pulse widthmodulation (PWM) signals that is provided as an input to generate thecoil drive signals.

In an embodiment, a wireless charging system may use a low-speed analogto digital converter (ADC) to measure high-speed signals from the coils.The ADC may have a maximum sampling speed that is lower than what isnecessary to accurately measure high-speed signals from the coils.However, using the digital processing methods discussed in the presentdisclosure, the wireless charging system may accurately reconstructamplitude and phase of the high-speed signals despite the limitations ofthe ADC.

In an embodiment, a wireless charging system may demodulatecommunication signals using a circuit with automatic gain control.Current through the coils in the wireless charging system is a functionof load controlled by a switch in the receiver devices, and by decodingpatterns in the current corresponding to ON/OFF patterns of the switch,the wireless charging system can recover communication signals from thereceiver devices. Because the current through the coils is dynamic, theautomatic gain control in the communication demodulation circuitimproves decoding accuracy. Further, the wireless charging system mayprocess the decoded signal for error correction at a bit-level and apacket-level.

In an embodiment, a wireless charging system may use machine learning todetect receiver devices on a charging surface of the wireless chargingsystem and select a charging configuration. The wireless charging systemmay allow the receiver devices to be placed at any location within thecharging surface. Because a various number of receiver devices may becharged and may be placed at different positions for different chargingsessions, it is difficult to analytically model interactions between aplurality of coils in the wireless charging system and a plurality ofreceiver devices. However, using a machine learning model to identify anappropriate charging configuration allows for effective wireless powerdelivery to the receiver devices for different device placements.

Throughout this specification, plural instances may implementcomponents, operations, or structures described as a single instance.Although individual operations of one or more methods are illustratedand described as separate operations, one or more of the individualoperations may be performed concurrently, and nothing requires that theoperations be performed in the order illustrated. Structures andfunctionality presented as separate components in example configurationsmay be implemented as a combined structure or component. Similarly,structures and functionality presented as a single component may beimplemented as separate components. These and other variations,modifications, additions, and improvements fall within the scope of thesubject matter herein.

As used herein any reference to “one embodiment” or “an embodiment”means that a particular element, feature, structure, or characteristicdescribed in connection with the embodiment is included in at least oneembodiment. The appearances of the phrase “in one embodiment” in variousplaces in the specification are not necessarily all referring to thesame embodiment.

Some embodiments may be described using the expression “coupled” and“connected” along with their derivatives. It should be understood thatthese terms are not intended as synonyms for each other. For example,some embodiments may be described using the term “connected” to indicatethat two or more elements are in direct physical or electrical contactwith each other. In another example, some embodiments may be describedusing the term “coupled” to indicate that two or more elements are indirect physical or electrical contact. The term “coupled,” however, mayalso mean that two or more elements are not in direct contact with eachother, but yet still co-operate or interact with each other. Theembodiments are not limited in this context.

As used herein, the terms “comprises,” “comprising,” “includes,”“including,” “has,” “having” or any other variation thereof, areintended to cover a non-exclusive inclusion. For example, a process,method, article, or apparatus that comprises a list of elements is notnecessarily limited to only those elements but may include otherelements not expressly listed or inherent to such process, method,article, or apparatus. Further, unless expressly stated to the contrary,“or” refers to an inclusive or and not to an exclusive or. For example,a condition A or B is satisfied by any one of the following: A is true(or present) and B is false (or not present), A is false (or notpresent) and B is true (or present), and both A and B are true (orpresent).

In addition, use of the “a” or “an” are employed to describe elementsand components of the embodiments herein. This is done merely forconvenience and to give a general sense of the invention. Thisdescription should be read to include one or at least one and thesingular also includes the plural unless it is obvious that it is meantotherwise.

Upon reading this disclosure, those of skill in the art will appreciatestill additional alternative structural and functional designs for asystem and a process for wireless charging through the disclosedprinciples herein. Thus, while particular embodiments and applicationshave been illustrated and described, it is to be understood that thedisclosed embodiments are not limited to the precise construction andcomponents disclosed herein. Various modifications, changes andvariations, which will be apparent to those skilled in the art, may bemade in the arrangement, operation and details of the method andapparatus disclosed herein without departing from the spirit and scopedefined in the appended claims.

What is claimed is:
 1. A computer-implemented method of training amachine-learned model configured to detect one or more receiver deviceson a charging surface of a wireless charging system and output a subsetfrom a plurality of coils of the wireless charging system for chargingthe one or more receiver devices comprising: obtaining a training dataset of desired charging configurations, the training data set includes aplurality of input data vectors associated with signals from theplurality of coils of the wireless charging system and a correspondingplurality of desired charging configurations that includes subsets ofcoils to be activated; and training a set of parameters of themachine-learned model using the training data set of desired chargingconfigurations, the training comprising repeatedly performing iterationsof: determining an estimated charging configuration by applying themachine-learned model with a set of parameters to an input data vectorfrom the training data set, determining a difference between theestimated charging configuration and the desired charging configurationassociated with the input data vector, and updating the set ofparameters of the machine-learned model to reduce the difference betweenthe estimated charging configuration and the desired chargingconfiguration associated with the input data vector.
 2. Thecomputer-implemented method of claim 1, wherein the signals from theplurality of coils of the wireless charging system are based on aposition of one or more receiver devices on the wireless chargingsystem.
 3. The computer-implemented method of claim 1, wherein the datavector is a concatenation of data from each of the plurality of coils ofthe wireless charging system.
 4. The computer-implemented method ofclaim 3, wherein the data vector includes a percentage of amplitudechange in a current signal of each of the plurality of coils.
 5. Thecomputer-implemented method of claim 3, wherein the data vectorsincludes a phase change in a current signal of each of the plurality ofcoils.
 6. The computer-implemented method of claim 1, wherein theplurality of coils of the wireless charging system are arranged in anarray such that adjacent coils in the array overlap each other.
 7. Thecomputer-implemented method of claim 6, wherein a distance between afirst coil and a second coil adjacent to the first coil is equal to anouter radius of the first coil and the second coil.
 8. A non-transitorycomputer-readable storage medium storing computer program instructionsexecutable to perform operations for training a machine-learned modelconfigured to detect one or more receiver devices on a charging surfaceof a wireless charging system and output a subset from a plurality ofcoils of the wireless charging system for charging the one or morereceiver devices, the operations comprising: obtaining a training dataset of desired charging configurations, the training data set includes aplurality of input data vectors associated with signals from theplurality of coils of the wireless charging system and a correspondingplurality of desired charging configurations that includes subsets ofcoils to be activated; and training a set of parameters of themachine-learned model using the training data set of desired chargingconfigurations, the training comprising repeatedly performing iterationsof: determining an estimated charging configuration by applying themachine-learned model with the set of parameters to an input data vectorfrom the training data set, determining a difference between theestimated charging configuration and the desired charging configurationassociated with the input data vector, and updating the set ofparameters of the machine-learned model to reduce the difference betweenthe estimated charging configuration and the desired chargingconfiguration associated with the input data vector.
 9. Thecomputer-readable storage medium of claim 8, wherein the signals fromthe plurality of coils of the wireless charging system are based on aposition of one or more receiver devices on the wireless chargingsystem.
 10. The computer-readable storage medium of claim 8, wherein thedata vector is a concatenation of data from each of the plurality ofcoils of the wireless charging system.
 11. The computer-readable storagemedium of claim 10, wherein the data vector includes a percentage ofamplitude change in a current signal of each of the plurality coils. 12.The computer-readable storage medium of claim 10, wherein the datavectors includes a phase change in a current signal of each of theplurality of coils.
 13. The computer-readable storage medium of claim 8,wherein the plurality of coils of the wireless charging system arearranged in an array such that adjacent coils in the array overlap eachother.
 14. The computer-readable storage medium of claim 13, wherein adistance between a first coil and a second coil adjacent to the firstcoil is equal to an outer radius of the first coil and the second coil.15. A system comprising: a processor; and a non-transitorycomputer-readable medium comprising computer program instructions thatwhen executed by the processor of an online system causes the processorto perform steps comprising: obtaining a training data set of desiredcharging configurations, the training data set includes a plurality ofinput data vectors associated with signals from the plurality of coilsof the wireless charging system and a corresponding plurality of desiredcharging configurations that includes subsets of coils to be activated;and training a set of parameters of the machine-learned model using thetraining data set of desired charging configurations, the trainingcomprising repeatedly performing iterations of: determining an estimatedcharging configuration by applying the machine-learned model with theset of parameters to an input data vector from the training data set,determining a difference between the estimated charging configurationand the desired charging configuration associated with the input datavector, and updating the set of parameters of the machine-learned modelto reduce the difference between the estimated charging configurationand the desired charging configuration associated with the input datavector.
 16. The system of claim 15, wherein the signals from theplurality of coils of the wireless charging system are based on aposition of one or more receiver devices on the wireless chargingsystem.
 17. The system of claim 15, wherein the data vector is aconcatenation of data from each of the plurality of coils of thewireless charging system.
 18. The system of claim 17, wherein the datavector includes a percentage of amplitude change in a current signal ofeach of the plurality of coils.
 19. The system of claim 17, wherein thedata vectors includes a phase change in a current signal of each of theplurality of coils.
 20. The system of claim 17, wherein resonantfrequencies of the plurality of coils of the wireless charging systemare selected to minimize mutual coupling between coils.